klinger.bib

@article{Troiano2023,
  author = {Enrica Troiano and Laura Oberl\"ander and Roman
                  Klinger},
  title = {Dimensional Modeling of Emotions in Text with
                  Appraisal Theories: Corpus Creation, Annotation
                  Reliability, and Prediction},
  journal = {Computational Linguistics},
  number = 1,
  volume = 49,
  month = mar,
  year = 2023,
  address = {Cambridge, MA},
  publisher = {MIT Press},
  abstract = {The most prominent tasks in emotion analysis are to
                  assign emotions to texts and to understand how
                  emotions manifest in language. An observation for
                  NLP is that emotions can be communicated implicitly
                  by referring to events, appealing to an empathetic,
                  intersubjective understanding of events, even
                  without explicitly mentioning an emotion name. In
                  psychology, the class of emotion theories known as
                  appraisal theories aims at explaining the link
                  between events and emotions. Appraisals can be
                  formalized as variables that measure a cognitive
                  evaluation by people living through an event that
                  they consider relevant. They include the assessment
                  if an event is novel, if the person considers
                  themselves to be responsible, if it is in line with
                  the own goals, and many others. Such appraisals
                  explain which emotions are developed based on an
                  event, e.g., that a novel situation can induce
                  surprise or one with uncertain consequences could
                  evoke fear. We analyze the suitability of appraisal
                  theories for emotion analysis in text with the goal
                  of understanding if appraisal concepts can reliably
                  be reconstructed by annotators, if they can be
                  predicted by text classifiers, and if appraisal
                  concepts help to identify emotion categories. To
                  achieve that, we compile a corpus by asking people
                  to textually describe events that triggered
                  particular emotions and to disclose their
                  appraisals. Then, we ask readers to reconstruct
                  emotions and appraisals from the text. This setup
                  allows us to measure if emotions and appraisals can
                  be recovered purely from text and provides a human
                  baseline. Our comparison of text classification
                  methods to human annotators shows that both can
                  reliably detect emotions and appraisals with similar
                  performance. Therefore, appraisals constitute an
                  alternative computational emotion analysis paradigm
                  and further improve the categorization of emotions
                  in text with joint models.},
  doi = {10.1162/coli_a_00461},
  url = {https://doi.org/10.1162/coli_a_00461},
  internaltype = {journal}
}
@article{troiano2022theories,
  title = {From theories on styles to their transfer in text:
                  Bridging the gap with a hierarchical survey},
  doi = {10.1017/S1351324922000407},
  journal = {Natural Language Engineering},
  publisher = {Cambridge University Press},
  author = {Troiano, Enrica and Velutharambath, Aswathy and
                  Klinger, Roman},
  year = {2022},
  pages = {1–60},
  url = {https://arxiv.org/abs/2110.15871},
  internaltype = {journal}
}
@article{terHorst2019,
  author = {Hendrik ter Horst and Matthias Hartung and Philipp
                  Cimiano and Nicole Brazda and Hans Werner M\"uller
                  and Roman Klinger},
  title = {Learning Soft Domain Constraints in a Factor Graph
                  Model for Template-based Information Extraction},
  journal = {Data \& Knowledge Engineering},
  year = {2019},
  volume = {125},
  pages = {101764},
  doi = {10.1016/j.datak.2019.101764},
  internaltype = {journal}
}
@article{Barnes2019,
  author = {Jeremy Barnes and Roman Klinger},
  title = {Embedding Projection for Targeted Cross-Lingual
                  Sentiment: Model Comparisons and a Real-World Study},
  journal = {Journal of Artificial Intelligence Research},
  year = {2019},
  volume = {66},
  pages = {691--742},
  month = {Nov},
  url = {https://doi.org/10.1613/jair.1.11561},
  doi = {10.1613/jair.1.11561},
  internaltype = {journal}
}
@article{Ehrlicher2019,
  author = {Hanno Ehrlicher and Roman Klinger and J\"org Lehmann
                  and Sebastian Pad\'o},
  title = {Measuring Historical Emotions and Their Evolution:
                  An Interdisciplinary Endeavour to Investigate The
                  `Emotions of Encounter'},
  journal = {Laborat\'orio Interdisciplinar sobre
                  Informa\,{c}\~{a}o e Conhecimento em revista (Liinc
                  em revista)},
  year = {2019},
  volume = {15},
  number = {1},
  pages = {},
  url = {http://revista.ibict.br/liinc/article/view/4557/4156},
  pdf = {http://revista.ibict.br/liinc/article/download/4557/4156},
  doi = {10.18617/liinc.v15i1.4557},
  internaltype = {journal}
}
@article{Kim2019b,
  author = {Evgeny Kim and Roman Klinger},
  title = {A Survey on Sentiment and Emotion Analysis for
                  Computational Literary Studies},
  journal = {Zeitschrift fuer Digitale Geisteswissenschaften},
  year = {2019},
  volume = {4},
  doi = {10.17175/2019_008_v2},
  internaltype = {journal}
}
@article{Kicherer2018,
  author = {Kicherer, Hanna and Dittrich, Marcel and Grebe,
                  Lukas and Scheible, Christian and Klinger, Roman},
  title = {What You Use, Not What You Do: Automatic
                  Classification and Similarity Detection of Recipes},
  journal = {Data and Knowledge Engineering},
  year = {2018},
  note = {in print},
  url = {https://doi.org/10.1016/j.datak.2018.04.004},
  pdf = {http://www.romanklinger.de/publications/kicherer2018preprint.pdf},
  internaltype = {journal}
}
@article{Bagewadi2014,
  author = {Shweta Bagewadi and Tamara Bobić and Martin
                  Hofmann-Apitius and Juliane Fluck and Roman Klinger},
  title = {Detecting miRNA Mentions and Relations in Biomedical
                  Literature [version 3; referees: 2 approved, 1
                  approved with reservations]},
  journal = {F1000Research},
  year = {2014},
  volume = {3},
  number = {205},
  doi = {10.12688/f1000research.4591.3},
  url = {http://f1000research.com/articles/3-205/v3},
  internaltype = {journal}
}
@article{Bobic2013,
  author = {Tamara Bobic and Roman Klinger},
  title = {Committee-based Selection of Weakly Labeled Instances for Learning
	Relation Extraction},
  journal = {Research in Computing Science},
  year = {2013},
  volume = {70},
  pages = {187-197},
  note = {Proceedings of the Conference on Intelligent Text Processing and
	Computational Linguistics},
  pdf = {http://www.romanklinger.de/publications/bobic-klinger-cicling2013.pdf},
  internaltype = {journal},
  url = {http://www.micai.org/rcs/2013_70/Committee-based%20Selection%20of%20Weakly%20Labeled%20Instances%20for%20Learning%20Relation%20Extraction.html}
}
@article{Hofmann2008,
  author = {Martin Hofmann-Apitius and Juliane Fluck and Laura
                  Furlong and Oriol Fornes and Corinna Kolarik and
                  Susanne Hanser and Martin Boecker and Stefan Schultz
                  and Ferran Sanz and Roman Klinger and Theo Mevissen
                  and Tobias Gatterneyer and Baldo Oliva and Christoph
                  Friedrich},
  title = {Knowledge Environments Representing Molecular
                  Entities for the Virtual Physiological Human},
  journal = {Philosophical Transactions of the Royal Society A},
  year = {2008},
  note = {PMID 18559317},
  doi = {10.1098/rsta.2008.0099},
  internaltype = {journal}
}
@article{Klinger2007b,
  author = {Roman Klinger and Laura I. Furlong and Christoph
                  M. Friedrich and Heinz Theodor Mevissen and Juliane
                  Fluck and Ferran Sanz and Martin Hofmann-Apitius},
  title = {Identifying Gene Specific Variations in Biomedical
                  Text},
  journal = {Journal of Bioinformatics and Computational Biology},
  year = {2007},
  volume = {5},
  pages = {1277-1296},
  number = {6},
  month = {December},
  note = {PMID 18172929},
  doi = {10.1142/S0219720007003156},
  pdf = {http://www.romanklinger.de/publications/snp_preprint.pdf},
  internaltype = {journal}
}
@article{Klinger2008,
  author = {Roman Klinger and Corinna Kolarik and Juliane Fluck
                  and Martin Hofmann-Apitius and Christoph
                  M. Friedrich},
  title = {{Detection of IUPAC and IUPAC-like Chemical Names}},
  journal = {Bioinformatics},
  year = {2008},
  volume = {24},
  pages = {i268-i276},
  number = {13},
  note = {Proceedings of the International Conference
                  Intelligent Systems for Molecular Biology (ISMB).},
  doi = {10.1093/bioinformatics/btn181},
  owner = {rklinger},
  timestamp = {2008.03.21},
  internaltype = {journal}
}
@article{Klinger2007,
  author = {Roman Klinger and G\"unter Rudolph},
  title = {{Automatic Composition of Music with Methods of
                  Computational Intelligence}},
  journal = {Transactions in Information Science and
                  Applications},
  year = {2007},
  volume = {4},
  pages = {508-515},
  number = {3},
  month = {March},
  internaltype = {journal}
}
@article{Kolarik2009,
  author = {Corinna Kolarik and Roman Klinger and Martin
                  Hofmann-Apitius},
  title = {{Identification of Histone Modifications in
                  Biomedical Text for Supporting Epigenomic Research}},
  journal = {BMC Bioinformatics},
  year = {2009},
  volume = {10},
  number = {S28},
  month = {January},
  note = {Proceedings of the Asia Pacific Bioinformatics
                  Conference (APBC)},
  doi = {10.1186/1471-2105-10-S1-S28},
  owner = {rklinger},
  publisher = {BioMed Central},
  internaltype = {journal}
}
@article{Larry2008,
  author = {Larry Smith and Lorraine K. Tanabe and Rie Johnson
                  nee Ando and Cheng-Ju Juo and I-Fang Chung and
                  Chun-Nan Hsu and Yu-Shi Lin and Roman Klinger and
                  Christoph M. Friedrich and Kuzman Ganchev and Manabu
                  Torii and Hongfang Liu and Barry Haddow and Craig
                  A. Struble and Richard J.  Povinelli and Andreas
                  Vlachos and William A. {Baumgartner Jr.} and
                  Lawrence Hunter and Bob Carpenter and Richard
                  Tzong-Han Tsai and Hong-jie Dai and Feng Liu and
                  Yifei Chen and Chengjie Sun and Sophia Katrenko and
                  Pieter Adriaans and Christian Blaschke and Rafel
                  Torres Perez and Mariana Neves and Preslav Nakov and
                  Anna Divoli and Manuel Mana and Jacinto Mata-Vazquez
                  and W. John Wilbur},
  title = {Overview of BioCreative II Gene Mention Recognition},
  journal = {Genome Biology},
  year = {2008},
  volume = {9},
  pages = {S2.2-S2.18},
  number = {Suppl 2},
  month = {September},
  doi = {10.1186/gb-2008-9-s2-s2},
  issn = {1465-6906},
  owner = {rklinger},
  url = {http://genomebiology.com/2008/9/S2/S2},
  internaltype = {journal}
}
@article{Thomas2011,
  author = {Philippe E. Thomas and Roman Klinger and Laura
                  I. Furlong and Martin Hofmann-Apitius and Christoph
                  M. Friedrich},
  title = {Challenges in the association of human single
                  nucleotide polymorphism mentions with unique
                  database identifiers},
  journal = {BMC Bioinformatics},
  year = {2011},
  volume = {12(Suppl 4)},
  number = {S4},
  doi = {10.1186/1471-2105-12-S4-S4},
  internaltype = {journal}
}